PLATCOV Statistical Analysis: Regeneron and Remdesivir
James Watson
11 October, 2022
1 Preamble
This Statistical Analysis Plan (SAP) is written for the PLATCOV trial (registered at ClinicalTrials.gov: https://clinicaltrials.gov/ct2/show/NCT05041907).
Data preparation is done in a different R script called data_prep.R. This Markdown script assumes that the data are saved in a .csv file interim_dat.csv in long format. The file interim_dat.csv contains the patient clinical and viral load data with the following column headers:
- ID: anonymized patient id code
- Time: time from randomization
- Trt: treatment allocation as written in CRF
- Site: site at enrollment
- Timepoint_ID: Day of study (integer 0 to 14)
- BARCODE: unique sample id code (in the following format: PLT-site-number-swab type-timepoint)
- Swab_ID: RTS or TSL (right versus left tonsil)
- Plate: unique Plate ID for the PCR assay (matching with plate identifiers in interim_control_dat.csv)
- Rand_date: date of randomization
- Any_dose: (0/1) any doses of any manufacturer received
- N_dose: integer number of doses received (any manufacturer)
- Antibody_test: 0/1 (negative/positive for SARS-CoV-2 antibody rapid test)
- Weight (kg)
- BMI: kg/weight^2
- Age: (years - has to be between 18-50)
- Sex: 0/1 (male: 1; female/other: 0)
- Symptom_onset: time since onset of symptoms (days)
- Variant: variant of concern (using standard WHO terminology for the main lineages, reference will be the predominant variant in the data set at the start of the study)
- CT_NS: observed CT value for the N/S gene
- CT_RNaseP: observed CT value for the human RNase P gene
- Per_protocol_sample: whether at the time of sampling the patient was still in per protocol with respect to drug dosing
- IgG: + IgG band on the LFT
- IgM: + IgM band on the LFT
- log10_viral_load: log10 number of viral copies per mL (estimated from control samples using a mixed effects model)
- log10_cens_vl: censoring value
1.1 Computational setup
## _
## platform x86_64-apple-darwin17.0
## arch x86_64
## os darwin17.0
## system x86_64, darwin17.0
## status
## major 4
## minor 0.2
## year 2020
## month 06
## day 22
## svn rev 78730
## language R
## version.string R version 4.0.2 (2020-06-22)
## nickname Taking Off Again## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] brms_2.17.0 Rcpp_1.0.9 plotrix_3.8-2
## [4] reshape2_1.4.4 RColorBrewer_1.1-2 loo_2.4.1
## [7] rstan_2.21.2 ggplot2_3.3.5 StanHeaders_2.21.0-7
##
## loaded via a namespace (and not attached):
## [1] nlme_3.1-153 matrixStats_0.61.0 xts_0.12.1
## [4] threejs_0.3.3 tensorA_0.36.2 tools_4.0.2
## [7] backports_1.2.1 bslib_0.3.0 DT_0.19
## [10] utf8_1.2.2 R6_2.5.1 DBI_1.1.1
## [13] colorspace_2.0-2 withr_2.5.0 tidyselect_1.1.1
## [16] gridExtra_2.3 prettyunits_1.1.1 processx_3.7.0
## [19] Brobdingnag_1.2-7 emmeans_1.6.3 curl_4.3.2
## [22] compiler_4.0.2 cli_3.3.0 shinyjs_2.0.0
## [25] sandwich_3.0-1 colourpicker_1.1.0 posterior_1.2.2
## [28] sass_0.4.0 scales_1.1.1 dygraphs_1.1.1.6
## [31] checkmate_2.0.0 mvtnorm_1.1-2 ggridges_0.5.3
## [34] callr_3.7.2 stringr_1.4.0 digest_0.6.29
## [37] rmarkdown_2.11 base64enc_0.1-3 pkgconfig_2.0.3
## [40] htmltools_0.5.2 fastmap_1.1.0 htmlwidgets_1.5.4
## [43] rlang_1.0.4 rstudioapi_0.13 shiny_1.6.0
## [46] jquerylib_0.1.4 farver_2.1.0 generics_0.1.0
## [49] zoo_1.8-9 jsonlite_1.8.0 gtools_3.9.2
## [52] crosstalk_1.1.1 dplyr_1.0.7 distributional_0.3.0
## [55] inline_0.3.19 magrittr_2.0.3 bayesplot_1.8.1
## [58] Matrix_1.3-4 munsell_0.5.0 fansi_1.0.3
## [61] abind_1.4-5 lifecycle_1.0.1 multcomp_1.4-17
## [64] stringi_1.7.4 yaml_2.2.1 MASS_7.3-54
## [67] pkgbuild_1.2.0 plyr_1.8.6 grid_4.0.2
## [70] parallel_4.0.2 promises_1.2.0.1 crayon_1.5.1
## [73] miniUI_0.1.1.1 lattice_0.20-44 splines_4.0.2
## [76] knitr_1.34 ps_1.7.1 pillar_1.8.1
## [79] igraph_1.2.6 estimability_1.3 markdown_1.1
## [82] shinystan_2.5.0 codetools_0.2-18 stats4_4.0.2
## [85] rstantools_2.1.1 glue_1.6.2 evaluate_0.16
## [88] V8_3.4.2 RcppParallel_5.1.4 vctrs_0.4.1
## [91] httpuv_1.6.3 gtable_0.3.0 purrr_0.3.4
## [94] assertthat_0.2.1 xfun_0.26 mime_0.11
## [97] xtable_1.8-4 coda_0.19-4 later_1.3.0
## [100] survival_3.2-13 rsconnect_0.8.24 tibble_3.1.8
## [103] shinythemes_1.2.0 TH.data_1.0-10 ellipsis_0.3.2
## [106] bridgesampling_1.1-2## Warning in checkStrict(calculate_fever_clearance): global variables used: ID,
## Time2 Overview of data
2.1 Load data
## All negative samples for id: PLT-TH1-128## PCR database contains data from 236 patients## we are missing patient PLT-TH1-056
## we are missing patient PLT-BR3-031##
## Favipiravir Fluoxetine Ivermectin
## 95 39 46
## Molnupiravir Nirmatrelvir + Ritonavir Nitazoxanide
## 23 20 8
## No study drug Regeneron Remdesivir
## 97 74 672.2 Data summaries
number of patients by analysis
## In the remdesivir analysis there are 131 patients (64 controls and 67 remdesivir)## In the regeneron analysis there are 158 patients (84 controls and 74 remdesivir)Display the per protocol matrix
## Number of patients per arm in modified intention to treat analysis## Include_mITT
## FALSE TRUE
## No study drug 4 91
## Regeneron 0 74
## Remdesivir 0 67## Number of swabs per protocol per treatment## PP_swabs
## 4 6 18 20
## No study drug 1 2 0 92
## Regeneron 0 0 1 73
## Remdesivir 0 0 0 67## In the mITT dataset we have 4638 PCR datapoints on 232 patients from 4 sites between 2021-10-02 and 2022-08-24:## N patients in mITT pop by site:##
## br003 th001 th057 th058
## 16 203 6 7##
## BA.1 BA.2 BA.4 BA.5 Delta
## No study drug 13 48 1 19 10
## Regeneron 15 30 0 16 13
## Remdesivir 20 37 0 0 10##
## Delta Omicron
## No study drug 10 81
## Regeneron 13 61
## Remdesivir 10 57##
## Delta Omicron_G446S Omicron_notG446S
## No study drug 10 13 68
## Regeneron 13 15 46
## Remdesivir 10 20 37## [1] TRUE## In the 232 patients, the geometric mean baseline (defined as samples taken within 6 hours of randomisation) viral load was 333936 copies per mL (95 percentile interval from 1736 to 64220513; range from 460 to 79656305)
Summary table
## [1] "Casirivimab\nimdevimab" "Remdesivir" "No study drug"## female is 59%## median age is 28 (IQR: 24-34)## median time since symptom onset is 2 (IQR: 2-3)## At least 1 vaccine is 97%## 25% 50% 75%
## 59020 374491 2664346## Censored values up until day 7:##
## left none
## 584 3588## The proportion censored is 14%## Variants in mITT database:##
## BA.1 BA.2 BA.4 BA.5 Delta
## 48 115 1 35 33## Variants in mITT database by treatment:##
## BA.1 BA.2 BA.4 BA.5 Delta
## Casirivimab\nimdevimab 15 30 0 16 13
## No study drug 13 48 1 19 10
## Remdesivir 20 37 0 0 10| Arm | n | Age | Baseline viral load (log10) | Number of vaccine doses | Antibody+ (%) | Male (%) | th001 | th057 | th058 | br003 |
|---|---|---|---|---|---|---|---|---|---|---|
| No study drug | 64 | 29.5 (20-50) | 5.5 (3-7.9) | 3 (0-4) | 94 | 42 | 52 | 3 | 2 | 7 |
| Remdesivir | 67 | 28 (19-49) | 5.5 (2.7-7.4) | 3 (0-4) | 90 | 48 | 54 | 2 | 2 | 9 |
| Arm | n | Age | Baseline viral load (log10) | Number of vaccine doses | Antibody+ (%) | Male (%) | th001 | th058 | th057 |
|---|---|---|---|---|---|---|---|---|---|
| Casirivimab | |||||||||
| imdevimab | 74 | 26 (18-48) | 5.7 (3-7.8) | 3 (0-5) | 88 | 36 | 70 | 3 | 1 |
| No study drug | 84 | 28.5 (18-46) | 5.5 (3-7.9) | 3 (2-5) | 95 | 40 | 79 | 2 | 3 |
| Arm | n | Age | Baseline viral load (log10) | Number of vaccine doses | Antibody+ (%) | Male (%) | th001 | th058 | th057 | br003 |
|---|---|---|---|---|---|---|---|---|---|---|
| Casirivimab | ||||||||||
| imdevimab | 74 | 26 (18-48) | 5.7 (3-7.8) | 3 (0-5) | 88 | 36 | 70 | 3 | 1 | 0 |
| No study drug | 91 | 29 (18-50) | 5.5 (3-7.9) | 3 (0-5) | 96 | 38 | 79 | 2 | 3 | 7 |
| Remdesivir | 67 | 28 (19-49) | 5.5 (2.7-7.4) | 3 (0-4) | 90 | 48 | 54 | 2 | 2 | 9 |
2.3 Summary data plot
This includes all patients in the mITT population with the per protocol swabs.
## Plotting data for 131 individuals## Plotting data for 158 individuals## Plotting data for 23 individuals## Plotting data for 26 individuals## Plotting data for 73 individuals
## Plotting data for 35 individuals3 Model fitting
3.1 Simple model using brms
Did this as a sanity check for handwritten models… basically gives the same results
3.2 Full analysis
The primary analysis consists of fitting a sequence of Bayesian hierarchical models to the mITT population (viral load data up until day 7, only patients who did not leave or switch before day 3).
There are a series of model fits, which are combinations of three models:
- Model 1: vanilla student-t regression with left censoring at 0 and with individual random effects for slope an intercept;
- Model 2: Linear model with additional RNaseP adjustment (this needs special treatment as we need to subtract the effect of RNaseP for the linear predictions);
- Model 3: Non-linear model (up and then down) with RNaseP adjustment.
two sets of priors:
- Weakly informative priors
- Quasi flat prior (multiply SDs by 10)
and two sets of covariate adjustments:
- basic covariate adjustment (slope and intercept):
- Variant (main Greek lineages as defined by WHO)
- Site
- Full covariate adjustment (slope and intercept), adding in:
- Vaccination (number of doses)
- Age (standardized to have mean=0 and sd=1)
- Time since symptom onset (days, between 0 and 4)
3.3 Specify priors
get priors
3.4 Prepare models
We make the stan data sets.
## In Remdesivir there are 2620 PCR datapoints and 131 patients
## Analysis dataset contains 131 patients and 2356 datapoints
## In Regeneron there are 3158 PCR datapoints and 158 patients
## Analysis dataset contains 158 patients and 2842 datapoints
## In REGN_Remdesivir_contemporaneous there are 3380 PCR datapoints and 169 patients
## Analysis dataset contains 169 patients and 3040 datapoints
## In Subgroup_Greek there are 3158 PCR datapoints and 158 patients
## Analysis dataset contains 158 patients and 2842 datapoints
## In Subgroup_G446S there are 3158 PCR datapoints and 158 patients
## Analysis dataset contains 158 patients and 2842 datapoints
## In Subgroup_Sublineages there are 3138 PCR datapoints and 157 patients
## Analysis dataset contains 157 patients and 2824 datapoints
## In Full there are 4638 PCR datapoints and 232 patients
## Analysis dataset contains 232 patients and 4172 datapoints## There are a total of 131 patients in the database with a total of 2356 PCRs analysable
## 14.56% (343 out of 2356) of samples are below LOD
## check stan data formatting:
## There are a total of 158 patients in the database with a total of 2842 PCRs analysable
## 11.65% (331 out of 2842) of samples are below LOD
## check stan data formatting:
## There are a total of 169 patients in the database with a total of 3040 PCRs analysable
## 11.88% (361 out of 3040) of samples are below LOD
## check stan data formatting:
## There are a total of 158 patients in the database with a total of 2842 PCRs analysable
## 11.65% (331 out of 2842) of samples are below LOD
## check stan data formatting:
## There are a total of 158 patients in the database with a total of 2842 PCRs analysable
## 11.65% (331 out of 2842) of samples are below LOD
## check stan data formatting:
## There are a total of 157 patients in the database with a total of 2824 PCRs analysable
## 11.44% (323 out of 2824) of samples are below LOD
## check stan data formatting:
## There are a total of 232 patients in the database with a total of 4172 PCRs analysable
## 14% (584 out of 4172) of samples are below LOD
## check stan data formatting:## There are a total of 158 patients in the database with a total of 2842 PCRs analysable
## 11.65% (331 out of 2842) of samples are below LOD
## check stan data formatting:## There are a total of 158 patients in the database with a total of 2842 PCRs analysable
## 11.65% (331 out of 2842) of samples are below LOD
## check stan data formatting:## There are a total of 157 patients in the database with a total of 2824 PCRs analysable
## 11.44% (323 out of 2824) of samples are below LOD
## check stan data formatting:3.5 Setup model runs
List all parameters settings for the model fitting:
## We are running all models with 4 chains and 4000 samples for each chain, discarding 2000 for burn-in and thining every 8, thus giving a total of 1000 posterior samples per model.All model fitting is run on a cluster using run_models.R (bmrc.sh provides bash commands)
Load model fits
4 Results
main models
4.1 Remdesivir
Plot the remdesivir versus no study drug output
## 2.5% 10% 50% 90% 97.5%
## 18 26 42 62 73## The model estimated population mean clearance half-life is 24.9 (95% CI 18.8-33.2)
## In No study drug the median clearance half life was 18 (range 3.6 to 46.7)
## In Remdesivir the median clearance half life was 12.8 (range 4.8 to 50)## The following `from` values were not present in `x`: Age_scaled, Antibody_test, Symptom_onset, N_dose
## The following `from` values were not present in `x`: Age_scaled, Antibody_test, Symptom_onset, N_dose##
## Subvariant BA.1 Subvariant BA.2 Subvariant BA.4 Subvariant BA.5
## 2.5% 0.50 0.97 0.36 0.29
## 10% 0.57 1.12 0.54 0.37
## 50% 0.77 1.48 0.98 0.69
## 90% 1.06 1.92 1.95 1.30
## 97.5% 1.24 2.21 2.78 1.71
##
## Siteth057 Siteth058 Sitebr003
## 2.5% 0.27 0.30 0.39
## 10% 0.34 0.36 0.46
## 50% 0.54 0.58 0.63
## 90% 0.84 0.92 0.87
## 97.5% 1.12 1.15 1.03##
## Subvariant BA.1 Subvariant BA.2 Subvariant BA.4 Subvariant BA.5
## 2.5% 0.93 1.07 0.35 0.60
## 10% 1.04 1.18 0.52 0.83
## 50% 1.27 1.43 0.98 1.35
## 90% 1.58 1.71 1.89 2.16
## 97.5% 1.76 1.88 2.72 2.75
##
## Siteth057 Siteth058 Sitebr003
## 2.5% 0.84 0.79 0.78
## 10% 0.99 0.93 0.87
## 50% 1.34 1.28 1.07
## 90% 1.83 1.76 1.32
## 97.5% 2.10 2.15 1.45
4.2 Regeneron
Same effect in all variants assumed
## 2.5% 10% 50% 90% 97.5%
## 8 13 25 39 46## The model estimated population mean clearance half-life is 17 (95% CI 13.6-21)
## In Casirivimab
## imdevimab the median clearance half life was 12.7 (range 5.8 to 27.7)
## In No study drug the median clearance half life was 16.2 (range 4.2 to 40.5)## The following `from` values were not present in `x`: Age_scaled, Antibody_test, Symptom_onset, N_dose
## The following `from` values were not present in `x`: Age_scaled, Antibody_test, Symptom_onset, N_dose##
## Subvariant BA.1 Subvariant BA.2 Subvariant BA.4 Subvariant BA.5
## 2.5% 0.49 0.85 0.39 0.57
## 10% 0.58 0.98 0.52 0.68
## 50% 0.80 1.29 0.95 0.91
## 90% 1.08 1.68 1.61 1.20
## 97.5% 1.26 1.89 2.25 1.41
##
## Siteth057 Siteth058 Sitebr003
## 2.5% 0.40 0.40 0.38
## 10% 0.50 0.52 0.54
## 50% 0.80 0.80 1.01
## 90% 1.27 1.34 1.90
## 97.5% 1.61 1.67 2.59##
## Subvariant BA.1 Subvariant BA.2 Subvariant BA.4 Subvariant BA.5
## 2.5% 0.77 0.76 0.81 0.83
## 10% 0.85 0.82 1.05 0.92
## 50% 1.01 0.96 1.62 1.08
## 90% 1.21 1.10 2.46 1.27
## 97.5% 1.34 1.20 3.04 1.39
##
## Siteth057 Siteth058 Sitebr003
## 2.5% 0.69 0.98 0.37
## 10% 0.81 1.15 0.51
## 50% 1.11 1.51 1.01
## 90% 1.48 1.97 2.02
## 97.5% 1.74 2.25 3.06
4.3 Both interventions together
Up until 10 June in Thai sites (where regeneron was available)
## 2.5% 10% 50% 90% 97.5%
## -49 -40 34 92 121## The model estimated population mean clearance half-life is 22.6 (95% CI 17.7-28.8)
## In Casirivimab
## imdevimab the median clearance half life was 12.9 (range 6.1 to 31)
## In No study drug the median clearance half life was 17.6 (range 3.8 to 42.7)
## In Remdesivir the median clearance half life was 13 (range 4.8 to 45.7)## probability that remdesivir is less than REGN in Delta:## [1] 0.942## probability that remdesivir is greater than REGN in Omicron:## [1] 0.9334.3.1 All data combined
## Ranking probabilities:##
## Remdesivir Casirivimab\nimdevimab (Delta) Casirivimab\nimdevimab (Omicron)
## 1 90 17 893
## 2 812 86 102
## 3 98 897 5
##
## No study drug (Delta) No study drug (Omicron) REGN (Delta)
## 10 81 13
## REGN (Omicron) Remdesivir
## 61 67## The model estimated population mean clearance half-life is 22.1 (95% CI 17.4-27.3)
## In No study drug (Delta) the median clearance half life was 21.8 (range 14.3 to 31.3)
## In No study drug (Omicron) the median clearance half life was 16.5 (range 3.9 to 43.1)
## In REGN (Delta) the median clearance half life was 12.4 (range 6.3 to 20)
## In REGN (Omicron) the median clearance half life was 13 (range 5.7 to 30.3)
## In Remdesivir the median clearance half life was 12.7 (range 4.9 to 45)## The following `from` values were not present in `x`: Antibody_test, N_dose
## The following `from` values were not present in `x`: Antibody_test, N_dose##
## Subvariant BA.1 Subvariant BA.2 Subvariant BA.4 Subvariant BA.5
## 2.5% 0.66 1.04 0.42 0.57
## 10% 0.76 1.19 0.53 0.67
## 50% 0.97 1.47 0.93 0.88
## 90% 1.29 1.84 1.62 1.12
## 97.5% 1.49 2.03 2.34 1.29
##
## Siteth057 Siteth058 Sitebr003 Age Days since\nsymptom onset
## 2.5% 0.31 0.35 0.45 0.97 0.54
## 10% 0.39 0.45 0.52 1.01 0.58
## 50% 0.59 0.67 0.71 1.10 0.65
## 90% 0.86 0.98 0.96 1.20 0.72
## 97.5% 1.07 1.17 1.14 1.25 0.76##
## Subvariant BA.1 Subvariant BA.2 Subvariant BA.4 Subvariant BA.5
## 2.5% 0.85 0.98 0.90 1.05
## 10% 0.94 1.05 1.14 1.14
## 50% 1.11 1.23 1.79 1.37
## 90% 1.33 1.45 2.81 1.65
## 97.5% 1.46 1.58 3.60 1.82
##
## Siteth057 Siteth058 Sitebr003 Age Days since\nsymptom onset
## 2.5% 0.88 1.00 0.80 0.90 0.93
## 10% 1.00 1.11 0.88 0.91 0.97
## 50% 1.28 1.41 1.06 0.96 1.03
## 90% 1.66 1.79 1.26 1.00 1.10
## 97.5% 1.95 2.02 1.41 1.02 1.14
4.4 Regeneron subgroups
4.4.1 Greek variant
##
## Casirivimab\nimdevimab (Delta) Casirivimab\nimdevimab (Omicron)
## 13 61
## No study drug (Delta) No study drug (Omicron)
## 10 81
## Remdesivir
## 67## The model estimated population mean clearance half-life is 19.6 (95% CI 14.5-26.1)
## In Casirivimab
## imdevimab (Delta) the median clearance half life was 12.3 (range 6.2 to 19.4)
## In Casirivimab
## imdevimab (Omicron) the median clearance half life was 13.1 (range 5.8 to 27.9)
## In No study drug (Delta) the median clearance half life was 20.8 (range 14.1 to 29)
## In No study drug (Omicron) the median clearance half life was 15.7 (range 4.2 to 40.3)4.4.2 G446S mutation
##
## Casirivimab\nimdevimab (Delta) Casirivimab\nimdevimab (G446S)
## 13 15
## Casirivimab\nimdevimab (not G446S) No study drug (Delta)
## 46 10
## No study drug (G446S) No study drug (not G446S)
## 13 68
## Remdesivir
## 67## The model estimated population mean clearance half-life is 18.8 (95% CI 14.2-24.5)
## In Casirivimab
## imdevimab (Delta) the median clearance half life was 12.3 (range 6.3 to 19.2)
## In Casirivimab
## imdevimab (G446S) the median clearance half life was 11.8 (range 7 to 27.8)
## In Casirivimab
## imdevimab (not G446S) the median clearance half life was 13.3 (range 5.8 to 24.2)
## In No study drug (Delta) the median clearance half life was 20.4 (range 13.8 to 29.2)
## In No study drug (G446S) the median clearance half life was 13.5 (range 7.5 to 23.2)
## In No study drug (not G446S) the median clearance half life was 16.5 (range 4.2 to 40.3)4.5 Sublineages subgroup analysis
##
## Casirivimab\nimdevimab (BA.1) Casirivimab\nimdevimab (BA.2)
## 15 30
## Casirivimab\nimdevimab (BA.5) Casirivimab\nimdevimab (Delta)
## 16 13
## No study drug (BA.1) No study drug (BA.2)
## 13 48
## No study drug (BA.5) No study drug (Delta)
## 20 10
## Remdesivir
## 67## The model estimated population mean clearance half-life is 18.6 (95% CI 14.2-24)
## In Casirivimab
## imdevimab (BA.1) the median clearance half life was 11.8 (range 7 to 28.2)
## In Casirivimab
## imdevimab (BA.2) the median clearance half life was 13.6 (range 6.3 to 24.9)
## In Casirivimab
## imdevimab (BA.5) the median clearance half life was 11.4 (range 5.7 to 21.8)
## In Casirivimab
## imdevimab (Delta) the median clearance half life was 12.2 (range 6.2 to 19.6)
## In No study drug (BA.1) the median clearance half life was 13.5 (range 7.5 to 23)
## In No study drug (BA.2) the median clearance half life was 18.1 (range 4.3 to 41.1)
## In No study drug (BA.5) the median clearance half life was 14.2 (range 7.9 to 28)
## In No study drug (Delta) the median clearance half life was 20.1 (range 13.9 to 28.4)4.5.1 Make main figure
## 2.5% 10% 50% 90% 97.5%
## All variants\n(n=67 vs n=64) 18 26 42 62 73
## All variants\n(n=74 vs n=84) 8 13 25 39 46
## Delta\n(n=13 vs n=10) 10 24 58 98 120
## Omicron\n(n=61 vs n=74) 3 7 20 33 43
## Delta\n(n=13 vs n=10) 8 22 50 86 109
## Omicron\nG446S mutated\n(n=15 vs n=11) -21 -11 8 39 59
## Omicron\nnot G446S mutated\n(n=46 vs n=63) 3 9 23 39 494.6 Slope fits
##
## Call:
## lm(formula = slope ~ Trt, data = plat_summary)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.39086 -0.11783 0.04102 0.18806 0.47932
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.47212 0.02610 -18.090 < 2e-16 ***
## TrtRegeneron -0.11932 0.03897 -3.062 0.00246 **
## TrtRemdesivir -0.16649 0.04008 -4.154 4.62e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.249 on 229 degrees of freedom
## Multiple R-squared: 0.0773, Adjusted R-squared: 0.06924
## F-statistic: 9.593 on 2 and 229 DF, p-value: 9.984e-05
##
## Pearson's product-moment correlation
##
## data: plat_summary$slope[ind] and plat_summary$clearance_time[ind]
## t = 0.68342, df = 127, p-value = 0.4956
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1135097 0.2309701
## sample estimates:
## cor
## 0.06053241